The background description provided herein is for the purpose of generally presenting the context of the disclosure. Work of the presently named inventors, to the extent the work is described in this background section, as well as aspects of the description that may not otherwise qualify as conventional art at the time of filing, are neither expressly nor impliedly admitted as conventional art against the present disclosure.
Recent developments in medical imaging include medical imaging modalities to to provide wider coverage, faster scan speed, improved spatial and temporal resolution, and reduced radiation dose. These developments not only provide better patient care, but also can potentially enable new scanning techniques and clinical applications. One trend across many modalities is the development of dynamic imaging techniques. In dynamic imaging, the patients are scanned at different points in time. A volume image (e.g., a three-dimensional snapshot) corresponding to each instant of time along a time series is then reconstructed. Functional information relevant to the medical condition of the patient can then be extracted from the time sequence of the images. For example, in a perfusion study, a perfusion map can be extracted from the time sequence of the images in the dynamic image. In X-ray computer tomography (CT), perfusion scans can provide information on the blood flow and blood supply to vital organs. In another example, dynamic positron emission tomography (PET) can be used to estimate kinetic parameters that might improve the detection and characterization of tumors. Other examples of dynamic medical imaging for which dynamic imaging can be beneficial include cardiac CT, subtraction CT, digital subtraction angiography (DSA), dynamic PET, and CT profusion studies in which X-ray CT is performed during the injection and dispersion of a contrast dye in the patient.
One common challenge for dynamic PET and CT is that taking many images, even if the images are acquired using relatively low radiation dosages, can result in a large accumulated radiation dosage. In both PET and CT, diagnostic image quality is achieved by using at least a minimum radiation dose for each snapshot. Improving denoising of the dynamic image will enable this minimum radiation dose for diagnostic image quality to be lower.
High radiation dosages in dynamic imaging could be a barrier to widespread adoption of these methods. To decrease the per image radiation dosage while maintaining diagnostic image quality, iterative reconstruction methods have been proposed to jointly reconstruct the entire 4D volume (e.g., three spatial dimensions and a time dimension) by using a motion model or a kinetic model. However, these approaches can be complex and incur high computational costs. Accordingly, these approaches have not been widely adopted for commercial scanners.
Thus, a tension exists between minimizing the radiation dosage to a patient while maintaining diagnostic image quality. On the one hand, maintaining a low radiation dosage for each image is important for ensuring that the total radiation dosage does not become too high. On the other hand, the signal-to-noise ratio becomes poorer as the radiation dosage decreases. Accordingly, methods of improving image quality without increasing the radiation dosage play an important role in striking a balance between maintaining a low radiation dosage to the patient while obtaining images with diagnostic image quality.